基于振荡统计矩的语音极性检测
Oscillating Statistical Moments for Speech Polarity Detection
摘要：
语音极性的反转可能对语音处理的各种技术的性能具有显著的不利影响。因此，需要一种用于确定语音极性（其取决于记录设置）的自动方法作为用于确保这种技术的良好行为的初步步骤。提出了一种基于振荡统计矩的极性检测方法。这些时刻具有在本地基频处振荡的性质，并且表现出取决于语音极性的相移。这种依赖性源于在矩计算中引入非线性或高阶统计量。所得到的方法显示在10个语音语料库，以提供一个实质性的改进相比，国家的最先进的技术。
英文摘要：
An inversion of the speech polarity may have a dramatic detrimental effect on the performance of various techniques of speech processing. An automatic method for determining the speech polarity (which is dependent upon the recording setup) is thus required as a preliminary step for ensuring the well-behaviour of such techniques. This paper proposes a new approach of polarity detection relying on oscillating statistical moments. These moments have the property to oscillate at the local fundamental frequency and to exhibit a phase shift which depends on the speech polarity. This dependency stems from the introduction of non-linearity or higher-order statistics in the moment calculation. The resulting method is shown on 10 speech corpora to provide a substantial improvement compared to state-of-the-art techniques.
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